A system tracks and controls access for supplying electrical power for charging devices associated with a user. The system has a server and one or more outlets. The outlets are connected to electrical power and are configured to supply electrical power to the devices. Each of the outlets has a socket configured to supply electrical power to the devices. Each of the outlets is further configured to transmit credentials to the server for authorization to access the outlet. The server is configured to determine whether the user is authorized to access the outlet and to transmit authorization to the outlet. The outlet is further configured to start a session and provide electrical power to the one or more devices upon receiving authorization from the server. The outlet is further configured to transmit information regarding the parameters to the server during the session.

Disclosed herein are AI-based platforms for enabling intelligent orchestration and management of power and energy. In various embodiments, an artificial intelligence system us configured to analyze a data set of monitored local conditions and generate a recommended configuration of at least one distributed system of a set of distributed systems, each distributed system of the set of distributed systems being configurable both to produce energy and to consume energy, wherein the configuration causes the at least one distributed system to produce and/or consume energy based on the monitored local conditions. In some embodiments, the artificial intelligence system configures a plurality of the distributed systems in the set such that a set of aggregate performance requirements are satisfied across the plurality. In some embodiments, the aggregate performance requirements are a set of economic performance requirements and/or a set of regulatory performance requirements.

An electrical power socket including: an electrical power outlet; a power input configured to supply power to the power outlet; one relay configured to control delivery of electrical power via the power outlet; a power monitor configured to monitor the operational state of the power outlet and characteristics of power drawn from the power outlet. The electrical power socket further includes: a microcontroller being configurable to: capture monitored data; send the captured data via a data network interface to a remote energy monitoring system; receive data from the remote energy monitoring system; and control the one relay to manage delivery of power via a power outlet responsive to a determination that the power outlet is delivering power associated with a wasted energy usage classification.

An electrical power socket including: an electrical power outlet; a power input configured to supply power to the power outlet; one relay configured to control delivery of electrical power via the power outlet; a power monitor configured to monitor the operational state of the power outlet and characteristics of power drawn from the power outlet. The electrical power socket further includes: a microcontroller being configurable to: capture monitored data; send the captured data via a data network interface to a remote energy monitoring system; receive data from the remote energy monitoring system; and control the one relay to manage delivery of power via a power outlet responsive to a determination that the power outlet is delivering power associated with a wasted energy usage classification.

A system is disclosed for monitoring a modular electrical power plant, the modular electrical power plant including at least two power generation units and an auxiliary system. The system for monitoring a modular electrical power plant includes a plurality of data collection channels for receiving data describing operating conditions of the at least two power generation units and a processing unit configured to generate a user interface. The user interface includes a single power generation unit view and a multiple power generation unit view. The processing unit is configured to select between the single power generation unit view and multiple power generation unit view based on the data describing the operating conditions of the at least two power generation units.

A system is disclosed for monitoring a modular electrical power plant, the modular electrical power plant including at least two power generation units and an auxiliary system. The system for monitoring a modular electrical power plant includes a plurality of data collection channels for receiving data describing operating conditions of the at least two power generation units and a processing unit configured to generate a user interface. The user interface includes a single power generation unit view and a multiple power generation unit view. The processing unit is configured to select between the single power generation unit view and multiple power generation unit view based on the data describing the operating conditions of the at least two power generation units.

The invention presents an energy management system for power distribution networks. It features a hierarchical network with multi-level metering nodes, each measuring energy usage. Data from these nodes are transmitted via a secure communication gateway to a cloud-based platform, which includes servers for processing and storage. A key component is a machine learning algorithm within the server, designed to analyze energy data, normalize and transform inputs, and identify anomalies. The algorithm generates anomaly scores for each power meter, reflecting potential operational issues. A user interface, accessible through client devices, displays the processed data and anomaly scores. This allows users to effectively monitor and manage the energy distribution, making informed decisions for optimization. The system enhances the efficiency and reliability of power distribution, offering advanced analysis and user-friendly monitoring capabilities.

The invention presents an energy management system for power distribution networks. It features a hierarchical network with multi-level metering nodes, each measuring energy usage. Data from these nodes are transmitted via a secure communication gateway to a cloud-based platform, which includes servers for processing and storage. A key component is a machine learning algorithm within the server, designed to analyze energy data, normalize and transform inputs, and identify anomalies. The algorithm generates anomaly scores for each power meter, reflecting potential operational issues. A user interface, accessible through client devices, displays the processed data and anomaly scores. This allows users to effectively monitor and manage the energy distribution, making informed decisions for optimization. The system enhances the efficiency and reliability of power distribution, offering advanced analysis and user-friendly monitoring capabilities.

The present disclosure relates to a method for determining a status of a power grid, wherein the power grid comprises a plurality of branches each connected between two buses. The method comprises obtaining current measurements of at least one of the plurality of branches, obtaining a grid model, the model comprising the plurality of branches and buses, estimating, using the grid model and the current measurements, a voltage value of at least one of the plurality of buses, obtaining, from a controller, at least one parameter of at least one of remaining branches of the plurality of branches, determining, based on the at least one parameter and current measurements of the at least one of the plurality of branches, currents of the remaining branches of the plurality of branches and determining or correcting the status of the remaining branches of the plurality of branches based on the estimated currents.

Disclosed herein are AI-based platforms for enabling intelligent orchestration and management of power and energy. In various embodiments, a set of edge devices is configured to communicate with at least one energy generation facility, energy storage facility, and/or energy consumption system and automatically execute a set of preconfigured policies that govern energy generation, energy storage, or energy consumption of the respective energy generation facilities, energy storage facilities, or energy consumption systems. In some embodiments, the automatically executed policies are a set of contextual policies that adjust based on the current status of a set of energy generation entities in an energy grid.